Forward Deployed Data Engineer, Qventus

• Proven experience as a data engineer or in a similar role, with a track record of building and maintaining large-scale data infrastructure
• Strong proficiency in SQL and Python for data processing and pipeline development
• Experience with cloud data platforms and services such as AWS (RDS, Redshift, Lambda, S3), GCP, or Azure
• Knowledge of both relational and non-relational databases (PostgreSQL, MySQL, MongoDB, etc.)
• Familiarity with modern data workflow orchestration tools (Airflow, DBT, Dagster, etc.)
• Ability to work closely with both technical and non-technical stakeholders to gather requirements and deliver solutions
• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent experience

Desirable

• Forward Deployed Data Engineers at Qventus collaborate directly with clients to identify their most critical data challenges and design scalable, high-performance pipelines and architectures to solve them
• Our customers depend on Qventus’ data infrastructure for mission-critical healthcare operations, and projects often start with broad, high-impact questions like, “How can we unify real-time surgical, staffing, and patient flow data into a single source of truth?” or “What’s the most efficient way to process and serve operational data for instant decision-making?”
• As a Data Engineer, you’ll combine technical expertise in large-scale data systems with a deep understanding of operational needs to create solutions that bridge the gap between raw data and actionable insights
• You’ll work closely with data scientists, software engineers, and product teams to ensure our data pipelines are robust, efficient, and ready to support advanced analytics, AI models, and production-grade applications
• You’ll operate in small, agile teams with significant autonomy, taking projects from initial scoping and design through to deployment and ongoing optimization
• A typical day might involve architecting cloud-based ETL workflows, optimizing query performance on multi-terabyte datasets, integrating disparate hospital data systems, or collaborating with client IT teams to ensure seamless adoption
• You'll design, build, and maintain scalable data pipelines and architectures to support analytics, machine learning, and operational applications
• Collaborate with cross-functional teams to translate complex operational needs into reliable, well-modeled datasets
• Integrate and normalize data from multiple structured and unstructured healthcare sources (EHRs, scheduling systems, operational databases, etc.)
• Optimize query performance and data processing for speed, scalability, and cost efficiency
• Implement best practices for data quality, governance, and security in compliance with healthcare regulations (e.g., HIPAA)
• Support deployment, monitoring, and troubleshooting of production data systems